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Ground wind vector nowcasting method based on SVR and VAR

A nowcasting and wind vector technology, applied in the field of machine learning, can solve problems such as VAR models cannot capture

Active Publication Date: 2021-06-18
郭洪涛
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Problems solved by technology

However, the relationship between surface meteorological elements is mainly nonlinear, and the traditional VAR model cannot capture

Method used

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  • Ground wind vector nowcasting method based on SVR and VAR

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Embodiment Construction

[0029] The technical solutions of the present invention will be further described below in conjunction with the drawings and examples. It should be understood that the following specific embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention.

[0030] The present invention proposes a surface wind vector nowcasting method based on SVR and VAR. The present invention optimizes the SVR technology for the characteristics of meteorological elements, and introduces and improves the VAR model to realize the forecast of the surface wind vector.

[0031] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. Work flow chart of the present invention is as figure 1 As shown, specifically:

[0032] First, collect the historical observation data of the site, including at least the observation values ​​of various meteorological elements on ...

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Abstract

The invention discloses a ground wind vector nowcasting method based on SVR and VAR. The method comprises the following specific steps and features: step 1, collecting various meteorological elements on the ground; step 2, carrying out ground wind vector decomposition and quality control; step 3, extracting significant independent variables based on single meteorological element SVR (Support Vector Register); step 4, carrying out non-linear model estimation based on all significant independent variables SVR and VAR; and step 5, performing recursive forecasting of the nonlinear model. According to the ground wind vector nowcasting method based on the SVR and the VAR, the SVR technology is optimized according to the characteristics of meteorological elements, a VAR model is introduced and improved, and forecasting of ground wind vectors is achieved.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a surface wind vector nowcasting method based on SVR and VAR. Background technique [0002] Wind vector (including wind speed and wind direction) is an important observation element of surface meteorological stations, and changes in surface wind vector can significantly affect social production and people's lives. For example, in the field of transportation, especially aviation, the enhancement or sudden change of surface wind not only affects the frequency of aircraft takeoff and landing, but also seriously threatens the safety of life and property. Another example is in the field of energy, the power sector needs to adjust the wind power generation plan according to the size of the surface wind, and reduce the potential risk of abnormal changes in the power generation of wind turbines to the transmission network. Therefore, there is an urgent need for surface wind vector foreca...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01W1/10
CPCG01W1/10Y02A90/10
Inventor 郭洪涛宋金杰
Owner 郭洪涛
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